This theme includes all OpenStreetMap features in this area matching ( Learn what tags means here ) :

tags['waterway'] IS NOT NULL OR tags['water'] IS NOT NULL OR tags['natural'] IN ('water','wetland','bay')

Features may have these attributes:

• name
• name:en
• waterway
• covered
• width
• depth
• layer
• blockage
• tunnel
• natural
• water
• source
• name:fil

This dataset is one of many "https://data.humdata.org/organization/hot">OpenStreetMap exports on HDX. See the Humanitarian OpenStreetMap Team website for more information.

This dataset contains a national-scale geodatabase of stream network and river catchment characteristics in the Philippines. It presents detailed information on 128 medium- to large-sized catchments (catchment area > 250 km2). The quantitative descriptions provide context for enabling geomorphologically-informed sustainable river management. The geodatabase provides a baseline understanding of fundamental topographic characteristics in support of varied geomorphological, hydrological and geohazard susceptibility applications. Data sets include: 1) GIS shapefiles with river catchment properties; 2) GIS shapefiles with stream network properties; 3) spreadsheets containing morphometric and topographic characteristics (n = 91); 4) example MATLAB code and topographic data to replicate the analysis for a selected catchment. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312/1.

¿Qué es el pH? ¿Cómo se mide? ¿Qué importancia tiene el pH en el agua?Diseño: Janina Guerrero (CEAZA). Contacto: janina.guerrero@ceaza.cl.

This map features a general, medium scale predictive soil layer suitable for mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for pH are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.More details on the Soil 250m pH can be found here.This web map can be used to provide context of the soil pH within the Central Asia and Caucasus region, where a user can refer to the legend to get a sense of the

This coverage shows the PH (The negative log of Hydrogen ion concentration) of soils in Kenya according to Kenya Soil Survey (KSS). Soil pH is determined by measuring the activity of H+ in a soil-water suspension.

This dataset consist of comma-separated values files containing the coordinate location of wells in Cebu and Mactan islands, Philippines expressed as points x (longitude) and y (latitude) in decimal degrees. The dataset is partitioned between a training and test subset at a proportion of 70% and 30%, respectively. The sources of the data were two government agencies tasked to manage the water resources in the Philippines. Shapefiles can be generated directly from the dataset using appropriate GIS software.Â

Soil_Samples_BACI

   Available only by request on a case by case basis. Contact rthe author, David Nowak, at dnowak@fs.fed.us



   Tags

   Biophysical Resources, Land, Social Institutions, Health, BES, Soil, Lead, Sample, UFORE




   Summary


   Samples were taken to relate soil data to vegetation data obtained for the Urban Forestry Effects Model (UFORE).


   Description


   The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg, K, Ca, and V. Soils were sampled in 125 plots located within the City of Baltimore in the summer of 2000. The plots were randomly stratified by Anderson Land Cover Classification System Level II, which included commercial, industrial, institutional, transportation right-of-ways, high and medium density residential (there were no low density residential areas identified within the city boundaries), golf course, park, urban open, forest, and wetland land-use types. The number of plots situated in each land-use type was weighted to their proportion of spatial area within the City. The resultant number of plots sampled for soil by land-use type was: commercial (n = 2); industrial (n = 3); institutional (n = 10); transportation right-of-ways (n = 7); high density residential (n = 19); medium density residential (n = 33); golf course (n = 3); riparian (n=2); park (n = 10); urban open (n = 10); and forest (n = 26) land-use types, respectively. The distribution of plots represents the proportion of area covered by impervious surfaces.


   Credits


   Rich Pouyat, USDA Forest Service


   Use limitations


   Not for profit use only


   Extent



   West -76.711030  East -76.530612 

   North 39.371355  South 39.200686 




   Scale Range

   There is no scale range for this item.



   The data is soil concentrations and characteristics of the following: land use, bulk density, sand, silt, clay, pH, organic matter, nitrogen, Al, P, S, Ti, Cr, Mn, Fe, Co, Ni, Cu Zn, Mo, Pb, Cd, Na, Mg, K, Ca, and V. Soils were sampled in 125 plots located within the City of Baltimore in the summer of 2000. The plots were randomly stratified by Anderson Land Cover Classification System Level II, which included commercial, industrial, institutional, transportation right-of-ways, high and medium density residential (there were no low density residential areas identified within the city boundaries), golf course, park, urban open, forest, and wetland land-use types. The number of plots situated in each land-use type was weighted to their proportion of spatial area within the City. The resultant number of plots sampled for soil by land-use type was: commercial (n = 2); industrial (n = 3); institutional (n = 10); transportation right-of-ways (n = 7); high density residential (n = 19); medium density residential (n = 33); golf course (n = 3); riparian (n=2); park (n = 10); urban open (n = 10); and forest (n = 26) land-use types, respectively. The distribution of plots represents the proportion of area covered by impervious surfaces.

Data gathered in the field during the sample collection phase of the National Geochemical Survey of Australia (NGSA) has been used to compile the Preliminary Soil pH map of Australia. The map, which was completed in late 2009, offers a first-order estimate of where acid or alkaline soil conditions are likely to be expected. It provides fundamental datasets that can be used for mineral exploration and resource potential evaluation, environmental monitoring, landuse policy development, and geomedical studies into the health of humans, animals and plants.

BPI Co. PORTS BREAKWATER

Maps with wind speed, wind rose and wind power density potential in The Philippines. The GIS data stems from the Global Wind Atlas (http://globalwindatlas.info/). GIS data is available as JSON and CSV. The second link provides poster size (.pdf) and midsize maps (.png).

Map with solar irradiation and PV power potential in the Philippines. The GIS data stems from the Global Solar Atlas (http://globalsolaratlas.info). The link also provides a poster size (.tif) and midsize map (.png). The Global Solar Atlas is continuously updated. Provided GIS data layers include long-term yearly average of: (1) PVOUT – Photovoltaic power potential kWh/kWp GHI – Global horizontal irradiation kWh/m2 DIF – Diffuse horizontal irradiation kWh/m2 GTI – Global irradiation for optimally tilted surface kWh/m2 OPTA – Optimum tilt to maximize yearly yield ° DNI – Direct normal irradiation [kWh/m2]

The Digital Surficial Geologic-GIS Map of Pictured Rocks National Lakeshore and Vicinity, Michigan is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (piro_surficial_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (piro_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (piro_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (piro_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (piro_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (piro_surficial_geology_metadata_faq.pdf). Please read the piro_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Western Michigan University. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (piro_surficial_geology_metadata.txt or piro_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Buoy layer

This map shows specific water-quality items and hydrologic data site information which come from QWDATA (Water Quality) and GWSI (Ground Water Information System). Both QWDATA and GWSI are subsystems of NWIS (National Water Inventory System)of the USGS (United States Geologic Survey).

This map is for Duchesne County, Utah.

The scope and purpose of NWIS is defined on the web site:

http://water.usgs.gov/public/pubs/FS/FS-027-98/

Map(s) of Field pH (saturated paste method) in bulk Top Outlet Sediment (TOS) and/or Bottom Outlet Sediment (BOS) samples. Source: The Geochemical Atlas of Australia (Caritat and Cooper, 2011)

The United States Geological Survey has published "An assessment of the representation of ecosystems in global protected areas using new maps of World Climate Regions and World Ecosystems" in Global Ecology and Conservation Journal. This work was produced by a team led by Roger Sayre, Ph.D., Senior Scientist for Ecosytems at the USGS Land Change Science Program with the support from The Nature Conservancy and Esri. We described this work using two introduction story maps, Introduction to World Ecosystems Map and Introduction to World Climate Regions Map. This story map is an introduction for World Climate Regions Map. You can have more information by accessing the published paper and you can access the dataset by downloading the pro package.

Hsu, I.C. (1971). Magnetic properties of igneous rocks in the Northern Philippines. Ph.D Thesis, Washington University, St.Louis 165 pp. Type: [ Outcrop ] Class: [ Extrusive ] Lithology: [ Extrusives ] Ages: [ 0 to 89 Ma N 5 ] from Earthref Magic

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

no abstract provided

To analyse the surface water quality of the area, we begin by identifying the sub-watersheds using Survey of India (SOI) Topographic Maps of 1:50,000 scale – 57 H5, 57 H6, 57 H7, 57 H9, 57 H10, 57 H11. Based on the drainage features of the area, the study area is demarcated into six sub-watersheds. Drainage map, Geology map, Contour map, and Digital Elevation Model (DEM) map are prepared using RS and GIS. Once the sub-watersheds are demarcated, surface water samples within these sub-watersheds are collected for further analysis as explained in the sections below. 30 samples were collected over a study period of two years covering three prominent seasons of pre-monsoon, monsoon, and post-monsoon periods. These samples were then subjected to various physical, chemical, and bacteriological tests such as pH, temp., DO, BOD, etc. (Bureau of Indian Standards: Public Safety Standards of the Republic of India: Chemical: Environmental Protection and Waste Management) to ascertain its usage for domestic purposes as well as for agricultural activities.